Bingqian Zou

Nanjing University of Aeronautics and Astronautics

Papers

Total Citations

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About

Bingqian Zou’s research bridges the frontiers of intelligent manufacturing and autonomous robotics, with a focus on optimizing production systems and enabling autonomous navigation. In their most-cited work, “Modeling and Optimization for Automobile Mixed Assembly Line in Industry 4.0” (2019, 26 citations), Zou addresses the digitization and networking of smart factories, modeling complex networks of production equipment, robots, conveyors, and logistics to enhance efficiency in mixed-flow assembly lines—a critical contribution to Industry 4.0. This work provides foundational optimization strategies for modern manufacturing. More recently, Zou explores autonomous exploration for Micro Aerial Vehicles (MAVs) with “LiDAR-Based Autonomous Exploration Using Local and Global RRT” (2021), integrating Rapidly-exploring Random Tree algorithms for real-time path planning in unknown environments. While early in impact, this work signals a shift toward field robotics and autonomous systems. Zou’s research demonstrates versatility across industrial optimization and robotic perception, offering practical solutions for smart factories and autonomous navigation. Their contributions are particularly valuable for researchers and students interested in the intersection of manufacturing systems, Industry 4.0, and robotic autonomy.